ClimART: A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models. - Salva Rühling Cachay; Venkatesh Ramesh; Jason N. S. Cole; Howard Barker; David Rolnick (NeurIPS Datasets and Benchmarks, 2021)

Generating physically-consistent high-resolution climate data with hard-constrained neural networks. - Paula Harder; Qidong Yang; Venkatesh Ramesh; Prasanna Sattigeri; Alex Hernández-García; Campbell D. Watson; Daniela Szwarcman; David S. Rolnick (CoRR, 2022)

ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning. - Julia Kaltenborn; Charlotte E. E. Lange; Venkatesh Ramesh; Philippe Brouillard; Yaniv Gurwicz; Chandni Nagda; Jakob Runge; Peer Nowack; David Rolnick (NeurIPS, 2023)

Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling. - Qidong Yang; Alex Hernández-García; Paula Harder; Venkatesh Ramesh; Prasanna Sattigeri; Daniela Szwarcman; Campbell D. Watson; David Rolnick (CoRR, 2023)

Hard-Constrained Deep Learning for Climate Downscaling. - Paula Harder; Alex Hernández-García; Venkatesh Ramesh; Qidong Yang; Prasanna Sattegeri; Daniela Szwarcman; Campbell D. Watson; David Rolnick (J. Mach. Learn. Res., 2023)

Tree semantic segmentation from aerial image time series. - Venkatesh Ramesh; Arthur Ouaknine; David Rolnick (CoRR, 2024)